--- title: "gpu-telemetry vs scalene" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/last9-gpu-telemetry-vs-plasma-umass-scalene" tools: ["last9-gpu-telemetry", "plasma-umass-scalene"] --- # gpu-telemetry vs scalene *GraphCanon updated Aug 9, 2026* ## Verdict Pick gpu-telemetry if gpu-telemetry provides comprehensive GPU observability in Kubernetes and Slurm environments by tying hardware metrics to the workload causing them; pick scalene if scalene is a high-performance CPU, GPU, and memory profiler for Python that uses AI to suggest optimizations. [gpu-telemetry](https://last9.io/gpu-observability/) reports 57 GitHub stars, 7 forks, and 5 open issues, last pushed Aug 2, 2026. [scalene](https://github.com/plasma-umass/scalene) has 13k stars, 435 forks, and 151 open issues, last pushed Aug 1, 2026. Figures are from public GitHub metadata via [gpu-telemetry's repository](https://github.com/last9/gpu-telemetry) and [scalene's repository](https://github.com/plasma-umass/scalene). | | [gpu-telemetry](/tools/last9-gpu-telemetry.md) | [scalene](/tools/plasma-umass-scalene.md) | | --- | --- | --- | | Tagline | GPU Observability with Workload Attribution | High-performance CPU, GPU, and memory profiler for Python with AI-powered optimization | | Stars | 57 | 13,485 | | Forks | 7 | 435 | | Open issues | 5 | 151 | | Language | Python | Python | | Adopt for | gpu-telemetry provides comprehensive GPU observability in Kubernetes and Slurm environments by tying hardware metrics to the workload causing them. | Scalene is a high-performance CPU, GPU, and memory profiler for Python that uses AI to suggest optimizations. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [gpu-telemetry](/tools/last9-gpu-telemetry.md) | [scalene](/tools/plasma-umass-scalene.md) | | --- | --- | --- | | Days since push | 6d | 2d | | Open issues (now) | 5 | 151 | | Full report | [trust report](/tools/last9-gpu-telemetry/trust.md) | [trust report](/tools/plasma-umass-scalene/trust.md) | ## Shared compatibility - **Python**: [gpu-telemetry](/tools/last9-gpu-telemetry.md) - Python runtime; [scalene](/tools/plasma-umass-scalene.md) - Python runtime ## Decision facts: gpu-telemetry - **Adopt for:** gpu-telemetry provides comprehensive GPU observability in Kubernetes and Slurm environments by tying hardware metrics to the workload causing them. ## Decision facts: scalene - **Adopt for:** Scalene is a high-performance CPU, GPU, and memory profiler for Python that uses AI to suggest optimizations. ## Choose when ### Choose gpu-telemetry if… - License: gpu-telemetry is MIT, scalene is Apache-2.0. - Tags unique to gpu-telemetry: amd, gpu-monitoring, intel-gaudi-base-operator, kubernetes. - When monitoring NVIDIA, AMD, or Intel Gaudi GPUs in Kubernetes clusters. ### Choose scalene if… - License: scalene is Apache-2.0, gpu-telemetry is MIT. - Tags unique to scalene: cpu-profiling, gpu-programming, memory-allocation, profiler. - When you need precise profiling of both CPU and GPU performance in Python applications ## When NOT to use gpu-telemetry - If your infrastructure is not based on Kubernetes or Slurm. - When you prefer tools that do not require per-node OTLP agents. - For environments without support for NVIDIA, AMD, or Intel Gaudi GPUs. ## When NOT to use scalene - If your project does not involve Python, as Scalene is specific to this language - Avoid if your system lacks necessary dependencies like Visual C++ Redistributable on Windows ## Common questions ### What is the difference between gpu-telemetry and scalene? gpu-telemetry: GPU Observability with Workload Attribution. scalene: High-performance CPU, GPU, and memory profiler for Python with AI-powered optimization. See the comparison table for live GitHub stats and shared categories. ### When should I choose gpu-telemetry over scalene? Choose gpu-telemetry over scalene when License: gpu-telemetry is MIT, scalene is Apache-2.0; Tags unique to gpu-telemetry: amd, gpu-monitoring, intel-gaudi-base-operator, kubernetes; When monitoring NVIDIA, AMD, or Intel Gaudi GPUs in Kubernetes clusters. ### When should I choose scalene over gpu-telemetry? Choose scalene over gpu-telemetry when License: scalene is Apache-2.0, gpu-telemetry is MIT; Tags unique to scalene: cpu-profiling, gpu-programming, memory-allocation, profiler; When you need precise profiling of both CPU and GPU performance in Python applications. ### When should I avoid gpu-telemetry? If your infrastructure is not based on Kubernetes or Slurm. When you prefer tools that do not require per-node OTLP agents. For environments without support for NVIDIA, AMD, or Intel Gaudi GPUs. ### When should I avoid scalene? If your project does not involve Python, as Scalene is specific to this language Avoid if your system lacks necessary dependencies like Visual C++ Redistributable on Windows ### Is gpu-telemetry or scalene more popular on GitHub? scalene has more GitHub stars (13,485 vs 57). Stars measure visibility, not whether either tool fits your constraints. ### Are gpu-telemetry and scalene open source? Yes - both are open-source projects on GitHub (gpu-telemetry: MIT, scalene: Apache-2.0). ### Where can I find alternatives to gpu-telemetry or scalene? GraphCanon lists graph-backed alternatives at [gpu-telemetry alternatives](/tools/last9-gpu-telemetry/alternatives) and [scalene alternatives](/tools/plasma-umass-scalene/alternatives) ([gpu-telemetry markdown twin](/tools/last9-gpu-telemetry/alternatives.md), [scalene markdown twin](/tools/plasma-umass-scalene/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/last9-gpu-telemetry-vs-plasma-umass-scalene.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, gpu-telemetry or scalene? gpu-telemetry: Very active. scalene: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for gpu-telemetry and scalene? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [gpu-telemetry trust report](/tools/last9-gpu-telemetry/trust); [scalene trust report](/tools/plasma-umass-scalene/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=last9-gpu-telemetry`](/api/graphcanon/graph?tool=last9-gpu-telemetry) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_